Hi there! 👋

I'm Nisa! I'm aspiring to become a data professional, and I'm all about that hustle to keep learning and growing in the data game. I'm diving into the world of data analysis, and data science, even though my formal education didn't exactly lead me down the computer science path. But guess what? I'm not letting that stop me!

✅ Competencies

Explotaroty Data Analysis, Data Preprocessing, Statistical Analysis, Data Visualization, Machine Learning, ETL/ELT, RDBMS, Business & Data Understanding, Data Mining, Big Data, CRISP ML (Q), Business Intelligence with Power BI, Data Visualization and Storytelling

💻 Tech Stack

Python, SQL (MySQL, MS SQL Server), BigQuery, Power BI, Tableau, Looker Studio, Streamlit, R

📂 Project Portfolio

Click here, please!

Nisa's Projects

capm-web-application-financial-analysis

This project showcases a web application that is designed to perform CAPM calculations for different stocks. The application uses Python programming language and its libraries such as Pandas, NumPy, Streamlit and Plotly, to gather stock data from Yahoo Finance and perform calculations to determine expected returns.

data-preprocessing-full-code

This file provides full practice of data preprocessing methods and techniques using different types of libraries.

data-viz-eda

This file provides data visualization using Python libraries and offers business moment decision examples.

malaysia-covid-19-dashboard

Malaysia COVID-19 Dashboard, a comprehensive platform created to provide timely and crucial insights into the COVID-19 situation in Malaysia. This dashboard offers real-time data on key COVID-19 metrics, including new active cases, new confirmed cases, new deaths, and recoveries.

nisa-g

Config files for my GitHub profile.

nisa-project-portfolio

This documentation provides a concise overview of my expertise and capabilities in the field of data, showcasing my skills and knowledge in this domain.

vix-data-analytics-accenture

Analysis of Social Buzz content categories that highlights the top 5 categories with the largest aggregate popularity. At the end of the project, we provide some recommendations to our clients to improve their business decisions.

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